Systems and methods for user-dependent conditioning of stimuli in tests using a method of continuous adjustment

ABSTRACT

Disclosed are systems and methods for user-dependent conditioning of stimuli in tests to elicit user responses to variations of one or more adaptive parameters of a user stimulus signal. The user stimulus signal is generated based on first and second adaptive parameters. The first adaptive parameter is modified to thereby generate a plurality of successive variations in the user stimulus signal, over one or more ranges of values of the second adaptive parameter. In response to modifying the first adaptive parameter, a plurality of user responses from a given user are received. Each user response indicates that one of the plurality of successive variations in the user stimulus signal has occurred. Based on an expected user response curve for the given user and a calculated time interval between successive user responses, an instantaneous rate of change for modifying the first adaptive parameter is adjusted such that the user responses are steered toward a neutral state around the expected user response curve.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.16/355,449, filed Mar. 15, 2019, entitled “SYSTEMS AND METHODS FORUSER-DEPENDENT CONDITIONING OF STIMULI IN TESTS USING A METHOD OFCONTINUOUS ADJUSTMENT”, which is a continuation-in-part of InternationalApplication Number PCT/EP2018/057339, filed Mar. 22, 2018 and entitled“METHODS FOR USER-DEPENDENT CONDITIONING OF STIMULI IN TESTS USING AMETHOD OF CONTINUOUS ADJUSTMENT”, the disclosure of which are hereinincorporated by reference in their entirety.

FIELD OF INVENTION

The disclosure relates generally to the field of digital signalprocessing (DSP), audio engineering and audiology, and more specificallypertains to systems and methods for continuous adaptation based on userperception of and response to stimulus.

BACKGROUND

Various behavioral methods have been developed in psychophysics toobtain psychometric data from observers, e.g., to measure a person'shearing ability. For example, conventional methods include the method oflimits, the method of constant stimuli, the method of adjustment, aswell as forced choice methods. In the context of measuring an observer'shearing threshold, Bekesy developed a method of “continuous adjustment”called “Bekesy tracking” [Bekesy, G. v., A new audiometer, ActaOto-Laryngologica, 35,41, 1-422. (1947)]. By way of a simple binaryinteraction of the user (pressing or releasing a single button), aparameter, i.e. the amplitude, of a sound stimulus is constantlyincreased or decreased resulting in an oscillation around a threshold.The threshold level can then be estimated from the points of userinteraction occurring above and below the threshold.

A “sweeping” Bekesy tracking paradigm represents a variant of thatgeneral method, where a second parameter of the stimulus (e.g.frequency) is constantly changed so that the level of the perceptualthreshold is traced along a range of values of that parameter of thestimulus.

Originally developed for estimating pure tone auditory thresholds, thegeneral mechanics of the Bekesy method, i.e. the continuous adjustmentof parameters of a stimulus based on user interaction, have also beenapplied in other contexts, e.g. for estimating psychophysical tuningcurves (PTC). [Sek, A., Alcantara, J., Moore, B. C. J., Kluk, K., &Wicher, A., Development of a fast method for determining psychophysicaltuning curves, International Journal of Audiology, 44(7), 408-420.(2005)]. Bekesy audiometry has been recognized as a useful diagnostictool in clinical audiology [see, e.g., Granitz, D. W. “An evaluation ofdiagnostic parameters of Bekesy audiometry”, LSU Historical DissertationTheses 2052 (1971)].

In a Bekesy tracking/continuous adjustment paradigm, for example, a useris tasked with pressing a button when he hears a sound and releasing thebutton when he does not. As long as the button is pressed, theparameter, i.e. the amplitude, of the stimulus is continuously reducedat a fixed rate until the user releases the button. When the button isreleased, the parameter, i.e. the amplitude, of the stimulus isincreased at the same rate. As a result of this procedure, the parameterof the stimulus should continuously oscillate around the threshold levelof a user at a given frequency.

Owing to its intuitive and engaging character, this method of continuoususer-controlled adjustment of the parameter of the stimulus lends itselfparticularly well for (but is not limited to) consumer (e.g. mobiledevice) implementations of psychometric tests, such as audiometrichearing tests. Users can quickly learn the task and are not required todirectly look at the device during a test, such that the user'scontinuous engagement allows for a large body of data to be collectedover a relatively short period of time. The conventional implementationof such a continuous user-controlled adjustment paradigm uses equalupward and downward rates of change of the user-controlled parameter ofa stimulus. Consequently, a “neutral” user interaction, i.e. pressingand releasing regularly and at uniform intervals, results in a flat(constant level) threshold estimate.

Generally, accuracy and reliability of the data in such a continuousadjustment paradigm is dependent on regularly occurring userinteraction, i.e. a threshold can only be reliably estimated in aparameter region where the user gives regular feedback. If the actualthreshold curve deviates significantly from the threshold levels thatwould be determined by “neutral” user interaction, users may onlyinteract with the test very rarely. In addition, data may exhibit anunpredictable bias when users become confused or disoriented after notinteracting with the test for longer periods of time.

The stimulus signal levels that a user can follow in a sweepingcontinuous adjustment paradigm, i.e. a paradigm wherein a secondparameter is continuously varied as the user's response to the stimulussignal levels is measured, may be technically limited by the fixed ratesof change of the stimulus level and the rate of change of the second,sweeping stimulus parameter. In particular, if the slope of the actualthreshold curve is similar to, or steeper than this technical limit, themeasured trace may not reflect the true thresholds beyond this limit.

Accordingly, it is an aspect of the present disclosure to providesystems and methods for obtaining a “neutral” response trace from theuser such that the neutral response trace follows a shape that is closerto the actual threshold curve of the user. Advantageously, the user willprovide more regular feedback, leading to more reliable data and lessbiased data. Such data can also allow for steeper threshold changes tobe followed.

SUMMARY OF THE INVENTION

According to aspects of the present disclosure, provided are systems andmethods that include a modification to a continuous adjustment paradigmin order to thereby facilitate “neutral” response behavior from a user.In some embodiments, the systems and methods include steps consistingof: estimating an initial expected response curve for a test of at leastone parameter of a stimulus for a particular user, based on prior dataand knowledge about that user; adjusting the rate of change of the oreach parameter of the stimulus in response to the regularity of userinteractions during the test in order to steer the user responsestowards the expected response curve to obtain more uniform intervalsbetween successive user interactions (“neutral” user interaction); andmodifying the initial expected response curve in accordance with thetest results when substantially neutral user interactions are notobtained across the test range for a selected parameter of the stimulus.

Neutral user interaction can be achieved by employing dissimilar ratesof change of a stimulus parameter when increasing and decreasing theparameter level to which the user responds during the test, and/or bymodifying the rate of change of this parameter depending on whether itis increasing or decreasing. In a sweeping auditory test, for example,this may mean adjusting separately for upward and downward sections ofthe sweeping auditory test, e.g. having faster rates of change instimulus levels during level increases and slower rates of change instimulus levels during level decreases. The performance of separateadjustments can steer the user response curve towards the expectedresponse curve for the test parameter. As a result, any non-neutralbehaviors of the user (test interaction at non-uniform intervals) willcorrespond to deviations of the actual trace from the initiallypredicted trace, and the predicted response contour can then be revisedaccordingly.

Aspects of the present disclosure thereby permit a continuous analysisof how well measured user response(s) match an initially expectedresponse contour. By analyzing the actual and predicted user responses,the expected response curve can be continually adjusted in order tomaximize the probability of obtaining an optimum data set for the user.In some embodiments, this may be achieved by a real-time windowedregression function calculation or LMS (least mean square) analysis ofthe user's responses against a dictionary, and/or may be achieved byutilizing a parametric model of actual responses from previous tests (ofthe same or other users) to dynamically adapt the expected responsecontour during the test.

A method of the present disclosure may include further modifying theexpected response curve in accordance with detected test results whensubstantially neutral user interaction is not obtained across the rangeof variation of the second variable parameter. The second variableparameter of the stimulus may be continuously varied monotonicallyacross the range of values for the test. The actual and expected userresponses and the degree of neutral user interaction may be continuouslyanalyzed and monitored, and the expected response curve may therefore becontinually adjusted to maximize the probability of obtaining neutraluser interaction across the range of values for the test.

In some embodiments, the rate of change of increases in the adaptiveparameter of the stimulus to meet the specified condition may beincreased when one or more expected response curves predict that thespecified condition will not be met, and neutral interaction will not beobtained without such increase.

In some embodiments, the rate of change of decreases in the adaptiveparameter of the stimulus after the specified condition has been met maybe decreased when one or more expected response curves predict that thespecified condition will not cease to be met (i.e. will continue to bemet), and neutral interaction will not be obtained without suchdecrease.

In some embodiments, systems and methods according to aspects of thepresent disclosure can be used for an audiometric test, wherein the testcomprises one or more of a supra-threshold test, a psychometric tuningcurve test, a masked threshold test, a temporal fine structure test, ora temporal masking curve test. In particular, the supra-threshold testmay be a psychometric tuning curve test or a masked threshold (MT) test.In some embodiments, the psychometric tuning curve test may be measuredfor signal tones between frequencies of 500 Hz and 4 kHz and at a soundlevel of between 20 dB SL and 40 dB SL, in the presence of a maskingsignal for the signal tone that sweeps from 50% of the signal tonefrequency to 150% of the signal tone frequency. In some embodiments, theMT test (a similar, albeit inverted paradigm to the PTC test) may bemeasured for a narrow band of noise between center frequencies of 500 Hzand 4 kHz while a probe tone sweeps from 50% of the noise band centerfrequency to 150% of the noise band frequency.

In some embodiments, the adaptive parameter of the stimulus may be anaudio signal amplitude. The second variable parameter of the stimulusmay be an audio tone frequency.

In some embodiments, the rate of change of the second variable parameterof the stimulus may also be varied to steer the user responses towardsneutral user interaction around the expected response curve with moreuniform intervals between successive user interactions.

In some embodiments, a method according to aspects of the presentdisclosure can be implemented under control of a software applicationfor use on a non-calibrated or unreferenced audio system and adapted fora user to self-administer the test.

In some embodiments, aspects of the present disclosure include systemsand methods for user-dependent conditioning of stimuli in a test toelicit user responses to variations of an adaptive parameter of astimulus utilizing a method of continuous adjustment to obtain aresponse curve indicative of the user's perception of the variations inthe adaptive parameter of the stimulus over a range of values of asecond variable parameter of the stimulus; the user responses comprisingbinary indications of whether or not the varying adaptive parameter ofthe stimulus meets a specified condition as the second variableparameter of the stimulus is also varied; each change of binaryindication being identified as a user interaction, the method beingdirected to obtain at least a predetermined number of user interactionsaround the response curve. The systems and methods can include stepsconsisting of: estimating the expected response curve for the user basedon prior data and knowledge about the test and the user; and adjustingthe rate of change of the adaptive parameter of the stimulus dependingon the regularity of user interactions during the test, the adjustmentsbeing directed to obtain at least a predetermined number of userinteractions over the range of values of the second variable parameterof the stimulus.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof, which areillustrated in the appended drawings. Understanding that these drawingsdepict only example embodiments of the disclosure and are not thereforeto be considered to be limiting of its scope, the principles herein aredescribed and explained with additional specificity and detail throughthe use of the accompanying drawings in which:

FIG. 1 illustrates user interactions in response to a Bekesy trackingmethod of continuous adjustment of a stimulus level at steady rates upand down over time;

FIG. 2 illustrates change of a second stimulus parameter over time,consistent with a “sweeping” Bekesy tracking paradigm;

FIG. 3 illustrates “neutral” user interactions in response to changes instimulus levels and frequency over a test frequency range;

FIG. 4 illustrates the problem whereby variations in a user'ssensitivity to changes in the adaptive parameters under a conventionalsweeping Bekesy paradigm lead to a loss of interaction;

FIG. 5 illustrates how a modified continuous adjustment method accordingto the invention results in extended user interaction;

FIG. 6 illustrates differing rates of change for stimulus level vs.frequency and frequency vs. time for a sweeping auditory threshold test;

FIG. 7 illustrates Psychometric Tuning Curve (PTC) test results forchanges in stimulus level and frequency with adaptive variation of amasker signal; and

FIG. 8 illustrates an example system for implementing one or moreaspects of the present disclosure.

DETAILED DESCRIPTION

Various example embodiments of the present disclosure are discussed indetail below. While specific implementations are discussed, theseimplementations are for illustration purposes only. One of ordinaryskill in the art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.

Disclosed are systems and methods for user-dependent conditioning ofstimuli in tests to elicit user responses to variations of an adaptiveparameter of a stimulus. By continuously adjusting the stimulus toobtain a response curve indicative of the user's perception of thevariations in the adaptive parameter of the stimulus, aspects of thepresent disclosure maximize regularity of user interactions around theresponse curve. Such improvements are particular desirable inaudiometric tests, including when such audiometric tests are carried outusing unreferenced or non-calibrated audio systems. Although theforthcoming discussion focuses on an exemplary such unreferenced ornon-calibrated audio system, the example is for purposes of illustrationand is not intended to be construed as limiting. It is appreciated thataspects of the present disclosure can further be applied in and used forsimilar test applications in other fields of sensory behavioral science,e.g. where a user interaction is measured in response to stimulusadaptations. In some embodiments, systems and methods of the presentdisclosure can include a computer program or mobile application on auser computing device, thereby allowing one or more user computingdevices to be used as a non-calibrated audio system for the user toperform self-administered tests.

The systems and methods according to aspects of the present disclosureaddress the problems of improving the efficiency and utility of tests,for example hearing tests, performed under uncertain conditions. Thesystems and methods in particular involve making predictions of anexpected test response curve, contour or profile for a user, based onprior data and knowledge about the user. The prior data may compriseinformation on the user's responses in previous tests, and/orcomparative information on test results from a database of other userswith similar socio-demographic profiles and pathology. Based on thepredictions, continuous real-time adjustments of one or more testparameters are made in substantially real-time, i.e. during a test, inorder to thereby steer user responses towards a predicted or expectedresponse contour of the user, thus maximizing user response symmetryaround an adaptive parameter of a stimulus.

The disclosure now turns to FIG. 1, which illustrates discrete userresponses 10,11 that are associated with changes in a stimulus level A(shown on the vertical axis) of a single adaptive parameter vs. time T(shown on the horizontal axis). For example, a single adaptive parametermight correspond to an audio signal amplitude or level at a specificpure tone frequency, although it is appreciated that various otheradaptive parameters can be utilized without departing from the scope ofthe present disclosure.

The user responses 10,11 are collected at discrete points in time. Forexample, user response 10 is measured when a user presses and holds abutton when the user determines that the audio tone of the hearing testreaches an audible level. User response 11 is measured when the userreleases the button, i.e. once the user determines that the audio toneof the hearing test is no longer audible (i.e. reaches an inaudiblelevel).

Between the released and pressed button states of user responses 10,11,the tone amplitude of the audio test is varied at one or more constantrates. In some embodiments, one or more of the constant rates can becalculated in accordance with a Bekesy tracking paradigm. Thus, when thebutton is released at user response 11, the stimulus level of the audiotone is then increased at a constant rate 12 until the user once againpresses and holds the button in response to being able to hear the audiotone of the hearing test. The stimulus level of the audio tone is thendecreased at a constant rate 13 until the user is no longer able to hearthe audio tone and releases the button. The cycle then repeats asdescribed above (although potentially with varying rates ofincrease/decrease in audio tone stimulus level) until the hearing testis terminated or otherwise concluded.

As can be seen in FIG. 1, the user response pairs (such as user responsepair 10,11) thereby oscillate consistently around a threshold level 14.

FIG. 2 illustrates the change of a second stimulus parameter over time,in a sweeping Bekesy paradigm. In particular, the second independentstimulus parameter in this case is frequency F, continuously varied overtime T. During the hearing test, the user thus responds to changes inthe first stimulus level as the second stimulus level is also changed.

FIG. 3 illustrates an example of what is referred to herein as “neutral”user interaction, where the user responses of pressing (i.e. userresponse 10) and releasing a button (i.e. user response 11) are measuredat regular intervals. In this case, the first stimulus level (i.e. audiosignal amplitude A) is varied up and down as the second stimulusparameter (i.e. audio tone frequency F) is continuously oscillatedbetween lower and higher levels. The threshold level associated withthis hearing test is thus also measured across a range of values of thesecond parameter (frequency F), thereby following a sweeping Bekesytracking paradigm.

As in the standard Bekesy tracking paradigm, the stimulus level of thefirst parameter (i.e., the stimulus level of the audio tone) isincreased at a constant rate 32 when the button is released and isdecreased at a constant rate 33 when the button is pressed. Throughoutthis variation of the first parameter, the second parameter (frequencyF) is monotonically increased. This results in a threshold curve 34 thatis calculated over a range of frequencies, rather than the singlethreshold level for a single frequency tone such as the one shown inFIG. 1. The user's interaction is “neutral” in this example (i.e.substantially the same as threshold curve 14 of FIG. 1), because thethreshold curve 34 in fact happens to be at a constant level across thislimited frequency range. This will not be so across the whole of anindividual's normal hearing range.

FIG. 4 illustrates on such example situation which arises when a user'sresponse curve to changes in the first parameter (audio tone level) of astimulus is not constant with respect to changes in the second parameter(audio tone frequency) of the stimulus. For example, this can occur whena user's audio threshold levels vary significantly at or between higherand/or lower frequencies. Thus, when the threshold curve 44 deviatessignificantly from a substantially constant level, the user interactionsof pressing 10, and releasing 11, the button become less regular andless frequent. Eventually, after a final button release 45, the user nolonger interacts with the audio test. In these circumstances, whilstresponse data allows reliable validation of the expected response curve44 a below a cut-off frequency 46, no data is obtainable to validate theresponse curve 44 b above the cut-off frequency 46. The reason for thislack of data lies in the fixed rates of increase 42 and decrease 43 ofthe stimulus level (i.e. the audio tone level). After the last userinteraction 45 with the button, the fixed rate of change of increase 42in the stimulus level with change in the frequency is actually less thanthe increase in the user's actual audio threshold level above thecut-off frequency 46. Thus, it is no longer possible to get any furtheruser interaction, data, or measurement using the standard Bekesyparadigm.

FIG. 5 illustrates an aspect of the present disclosure that solves thisproblem and extends the range of user interaction to obtain appropriatedata beyond the cut-off frequency 46 by using a modified Bekesyparadigm. In this example, the increases and decreases in the stimuluslevel are not necessarily kept constant throughout (as in the standardBekesy paradigm illustrated in FIG. 4), but are themselves adaptive andvariable in real-time, according to one or more predicted and/ordetected variations in rate of change of a user's threshold responsecurve 54 for the measured parameter. Accordingly, the audio tonestimulus level increases 52 a,b,c are each associated with asuccessively larger rate of change, with 52 a being the relativelysmallest rate of change and 52 c being the relatively largest rate ofchange. Similarly, the audio tone stimulus level decreases 53 a,b,c areeach associated with a successively smaller rate of change, with 53 abeing the relatively largest rate of change and 53 c being therelatively smallest rate of change.

Thus, where the user's threshold response level 54 is only slowlyincreasing (i.e., at lower frequencies; the left-hand portion of thegraph of FIG. 5), the rates of change 52 a, 53 a up or down of the audiotone stimulus level are still relatively constant, as in the standardBekesy paradigm. However, where the user's threshold levels arepredicted, or detected, to be increasing more rapidly (e.g. around thecut-off frequency 46), the respective rates of change of increasing anddecreasing audio tone stimulus levels diverge. Rates of change forincreasing levels 52 b, 52 c (after button releases) are steeper; ratesof change for decreasing levels 53 b, 53 c (after button presses) areflatter or slower, and steered towards the expected response curve 54.Through this modification, it is possible to generate more regular andconsistent user data from the hearing test. In this particular example,when the actual threshold trace follows the expected threshold trace,the user is able to continue to interact and generate regular datapoints beyond the previous final data point 45, thereby allowingvalidation of the user response curve 54 beyond the previous limitimposed by cut-off frequency 46.

FIG. 6 illustrates an example of adaptive parameters (in this example,audio stimulus level 61 and audio tone frequency 62) being varied atdifferent rates. In the above discussion of FIG. 5, the rates of changeof audio tone stimulus level were varied while increasing or decreasingthe level, but frequency was varied in a constant manner. However, insome embodiments, the rates of change of frequency may be varied forspecific stimulus levels instead, or the rates of change for both theaudio tone level parameter and the audio tone frequency parameter may bevaried.

Note also that, if the measured levels of an adaptive parameter areexpected to drop off steeply with changes in a second parameter, thenrather than increasing the rate of change of the parameter upwards anddecreasing the rate of change downwards (c.f. FIG. 5), it may benecessary to follow the opposite procedure—i.e. to increase the rate ofchange downwards and decrease the rate of change upwards.

It is also possible to adjust the rates of variation or sweep of any ofthe parameters during tests to obtain data meeting a desired qualitycriterion. For example, such a criterion could be a minimum total numberof user interactions (i.e. data points). Thus, for example, a test maybe performed more rapidly for an individual who is fully able, whereas atest may need to be carried out more slowly for users who have some formof physical or cognitive impairment, in order for both tests to generatedata meeting one or more same/similar desired quality criterion. Forexample, the second parameter value (audio tone frequency) may bechanged or swept more slowly or more rapidly, depending on the rate andregularity of user interactions, in order to thereby obtain at least apredetermined number of user interactions over the range of values ofthe second variable parameter of the audio tone stimulus (e.g. a minimumtotal number necessary to fully validate a user's response curve).

Various audiometric tests may benefit from using modified Bekesytracking in accordance with one or more aspects of the presentdisclosure. For example, such audiometric tests include, but are notlimited to, Psychometric Tuning Curve (PTC) tests. Other suchaudiometric tests include, but are not limited to, supra-thresholdtests, temporal fine structure tests, masked threshold tests andtemporal masking curve tests.

A PTC test may typically be performed for audio and/or signal tonesbetween frequencies of 125 Hz and 16 kHz, in some embodiments betweenfrequencies of 250 Hz and 8 kHz, and in some embodiments preferablybetween frequencies of 500 Hz and 4 kHz. A PTC test may be performed atany audio/signal tone level above the user's hearing threshold (i.e. anylevel above 0 dB SL), in some embodiments at signal levels between 10 dBSL and 60 dB SL, and in some embodiments preferably at signal levelsbetween 20 dB SL and 40 dB SL, with a masking signal applied to sweep ina predefined range around each signal tone frequency, particularly from50% of the signal tone frequency to 150% of the signal tone frequency.

In some embodiments, the masking signal can be applied to sweep aroundeach signal tone frequency in a range of 60% of the signal tonefrequency to 140% of the signal tone frequency, particularly between 80%of the signal tone frequency to 120% of the signal tone frequency.

The signal level of the masking signal is continuously modulatedaccording to a user's responses to the audio/stimulus tone of the PTCtest. For example, if the user indicates that he can detect the signaltone, then the masker signal level is increased; if the user indicatesthat he cannot detect the signal tone, then the masker signal level isdecreased. A similar approach can be used for the masked threshold (MT)test, which uses an inverted PTC paradigm in which a narrow band ofnoise with a center frequency is held at a constant frequency while aprobe tone sweeps around each noise band.

In a calibrated system, more reliable data can be obtained by modulatingthe masker intensity (i.e. the signal level of the masking signal)around a curve that would provide a constant output in dB HL. This is sothat the user does not experience any jumps in intensity due todiscontinuities in the frequency response of the hardware setup, or dueto differences in human sensitivity to tones of different frequency.

In an uncalibrated audio system however (assuming the output of theaudio system is at least reasonably flat across frequency), andparticularly given that the precise output level at each frequency isunknown in an un-calibrated system as explained above. For example,International Patent Application PCT/EP2017/076679 (filed Oct. 19, 2017and herein incorporated by reference in its entirety) discloses that itis advantageous if the masker intensity is modulated relative to astandard weighting curve, such as for example A-weighting, such asdefined in IEC 61672:2003, or an equal loudness contour, such as definedin IS0226. This provides a consistent feel of control of the maskerintensity to the user across the frequency range of the test and yieldsmore reliable results. It will be readily apparent that modified Bekesytracking in accordance with the methods of the invention may alsoenhance such test results.

A temporal masking curve test involves a forward-masking task wherebythe masker level required to mask a fixed, low-level pure-tone probe ismeasured as a function of the masker-probe interval to produce atemporal masking curve. Limiting the probe to a low level minimizesspread of excitation along the basilar membrane and effects ofoff-frequency listening. As the probe level is fixed, the requiredmasker level increases with increasing masker-probe interval, resultingin temporal masking curves that have positive slopes. For anoff-frequency masker, which is assumed to be processed linearly, thetemporal masking curve is assumed to reflect decay of masking. As themasker-probe interval is increased, the masker level required at maskedthreshold increases to compensate for the time course of decay. For anon-frequency masker, the temporal masking curve is assumed to reflectthe combined effects of the decay of masking and compression applied tothe masker. Therefore, a larger change in masker level would be requiredto produce a given change in basilar membrane excitation when theresponse to the masker is compressive. This would be reflected as asteeper on-frequency temporal masking curve compared to an off-frequencytemporal masking curve. Assuming the time course of decay of the maskeris identical for all masker frequencies (and levels), the degree ofbasilar membrane compression can be estimated by comparing the slope ofa temporal masking curve for an on-frequency masker against the slope ofa temporal masking curve for a masker that is processed linearly by thebasilar membrane (i.e. off-frequency masker or linear-reference temporalmasking curve). Basilar membrane responses can be inferred by plottingthe off-frequency masker level against the on-frequency masker levelrequired for each masker-probe interval.

Where the present disclosure is applied to an audiometric test that is atemporal masking curve test (rather than the PTC test described above),the rate of change of the masker level and the masker-probe intervalcould be varied as the adaptive parameters of the stimulus.

Although the description with reference to FIG. 6, above, is exemplifiedusing potential adaptive parameters of audio stimulus level 61 and audiotone frequency 62, it is appreciated that the test is applicable to anypsychophysical test in which a threshold in sensory perception of afirst factor is determined while second and third factors are changingover time.

For example, visual tests such as contrast sensitivity tests would beequally applicable. In a test of this nature, the ability to distinguishtwo lines as distinct objects with varying color and/or intensity can betested. In this case the adaptive parameters of the stimulus could bethe hue (i.e. the frequency) of the line and the distance between thelines. As another option this test could use, as adaptive parameters,the intensity (typically measured in lumens) of the lines and thedistance between the lines. Alternatively, or additionally, the abilityto read text of varying color and intensity against a specificbackground could be tested. In this case the adaptive parameters of thestimulus could be the text hue and the background hue. As another optionthis test could use, as adaptive parameters, the text intensity and thebackground intensity. In a similar manner to that described above withreference to the auditory example of FIG. 6, the user response can besteered towards the predicted or expected response contour of the user,i.e. the user presses a button when he sees the distinct objects andreleases the button when he can no longer see the distinct objects,while color and intensity are varied over time. Further examples mayinclude, but are not limited to visual acuity, where the object size andfocus length are variables; peripheral vision, where the object size andangle from central vision are variables; color vision, where the colorand intensity of two light sources are varied to match a third source;and taste or smell where the presence of a first smell or taste istested using the variables of concentration and location.

FIG. 7 illustrates a PTC audiometric test measurement 100. The diagramshows the audio level or intensity A in arbitrary units on thevertical-axis, against audio frequency F on the horizontal-axis. Asillustrated, a signal tone 102 at a first sound level 101 is masked by amasker signal 105 particularly sweeping 103 through differentfrequencies in the proximity of the signal tone 102. The test userindicates at which sound level he hears the signal tone over the maskersignal. The signal tone and the masker signal are well within the user'shearing range.

While a signal tone 102 of a constant frequency and intensity 101 isplayed to the user, a masker signal 105 slowly sweeps 103 from afrequency lower to a frequency higher than the signal tone 102. The rateof sweeping 103 may be constant or may be varied in response to theconsistency of the user's interactions. The goal for the user is to hearthe signal tone 102. When the user can no longer hear the signal tone102 (e.g. as indicated by the user by releasing a pushbutton) the maskersignal intensity is reduced 104 to a point where the user starts hearingthe signal tone 102 (indicated by the user by pressing the pushbutton).While the masker signal tone 105 is still sweeping 103 upwards infrequency, the intensity of the masker signal 105 is increased 104again, until the user no longer hears the signal tone 102 again. Thisway, the masker signal intensity oscillates 106 around the user'sexpected or predicted hearing level response curve 107 (as indicated bythe solid line). This hearing level response curve 107 can be comparedwith a well-established and well-known response curve for people havingno hearing loss. Any deviations from this known curve would beindicative of a hearing loss.

In some embodiments, it is desirable that the initial and/or expecteduser response curves and profiles for changes in one parameter over arange of variation of a second parameter should be predicted withsufficient accuracy to facilitate substantially neutral user interactionacross a desired test range. For audiometric purposes, or for example,for threshold curves in Pure Tone Threshold tests, supra-threshold tests(e.g. Psychometric Tuning Curve tests), or equal loudness contour tests,such predictions may be based on information of various types, such as:

-   -   ISO7029: Acoustics—Statistical distribution of hearing        thresholds as a function of age;    -   IS0226: Acoustics—Normal equal loudness contours;    -   prior test results (and particularly confirmed clinical-standard        pure tone audiometry) from cohorts of other patients with        similar characteristics;    -   Other available meta-information about the data sets, including:        -   Reaction times        -   Estimated accuracy of data set        -   Time of day        -   Geographic location        -   Test duration        -   Number of interruptions        -   Demographic user information    -   Socio-demographic factors, such as:        -   age of the user        -   sex of the user        -   the cognitive capacity of the user        -   genetic disposition of the user, possibly affecting hearing            ability        -   genomic information for the user        -   working environment        -   leisure activities        -   music listening habits (types, loudness, frequency)        -   telephone setting preferences (loudness)        -   chronic or acute illnesses, pathologies affecting hearing            ability        -   prescription/recreational drug use (including alcohol)    -   Performance details for the user's audio equipment (e.g. mobile        audio device and headphones)

A computer program, or mobile device application (“App”) comprisingcomputer program code, may be provided to allow a user toself-administer tests using the methods according the invention, whenthe computer program is loaded, streamed or executed on a personalcomputer or mobile device.

FIG. 8 illustrates an example system embodiment in which various aspectsof the present disclosure can be implemented. Persons of ordinary skillin the art will also readily appreciate that other system embodimentsare possible. Depicted is a system bus computing system architecture 800wherein the components of the system are in electrical communicationwith each other using a bus 805. Exemplary system 800 includes aprocessing unit (CPU or processor) 810 and a system bus 805 that couplesvarious system components including the system memory 815, such as readonly memory (ROM) 820 and random access memory (RAM) 825, to theprocessor 810. The system 800 can include a cache of high-speed memoryconnected directly with, in close proximity to, or integrated as part ofthe processor 810. The system 800 can copy data from the memory 815and/or the storage device 830 to the cache 812 for quick access by theprocessor 810. In this way, the cache can provide a performance boostthat avoids processor 810 delays while waiting for data. These and othermodules can control or be configured to control the processor 810 toperform various actions. Other system memory 815 may be available foruse as well. The memory 815 can include multiple different types ofmemory with different performance characteristics. The processor 810 caninclude any general-purpose processor and a hardware module or softwaremodule, such as module 1 832, module 2 834, and module 3 836 stored instorage device 830, configured to control the processor 810 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. The processor 810 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

To enable user interaction with the computing device 800, an inputdevice 845 can represent any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 835 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems can enable a user to provide multiple types of input tocommunicate with the computing device 800. The communications interface840 can generally govern and manage the user input and system output.There is no restriction on operating on any particular hardwarearrangement and therefore the basic features here may easily besubstituted for improved hardware or firmware arrangements as they aredeveloped.

Storage device 830 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs) 825, read only memory (ROM) 820, andhybrids thereof.

The storage device 830 can include software modules 832, 834, 836 forcontrolling the processor 810. Other hardware or software modules arecontemplated. The storage device 830 can be connected to the system bus805. In one aspect, a hardware module that performs a particularfunction can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 810, bus 805, display 835, and soforth, to carry out the function.

It will further be appreciated by those skilled in the art that althoughthe invention has been described by way of example with reference toseveral embodiments it is not limited to the disclosed embodiments andthat alternative embodiments could be constructed without departing fromthe scope of the invention as defined in the appended claims.

The presented technology offers a novel and convenient way to provideadded clarity to the telephonic communications of receivers who maysuffer from known or undiagnosed hearing deficiencies by seamlesslypersonalizing phone calls. It is to be understood that the presentdisclosure contemplates numerous variations, options, and alternatives.For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral-purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example. The instructions, media for conveyingsuch instructions, computing resources for executing them, and otherstructures for supporting such computing resources are means forproviding the functions described in these disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

What is claimed is:
 1. A method comprising: generating a user stimulussignal according to a first adaptive parameter and a second adaptiveparameter; modifying the first adaptive parameter in order to generate aplurality of successive variations in the user stimulus signal, suchthat the plurality of successive variations in the user stimulus signalare generated over one or more given ranges of values of the secondadaptive parameter; receiving, in response to modifying the firstadaptive parameter, a plurality of user responses from a given user,each user response indicating that a corresponding one of the pluralityof successive variations in the user stimulus signal has occurred; andbased at least in part on an expected user response curve for the givenuser and a calculated time interval between successive ones of theplurality of user responses received from the given user, adjusting aninstantaneous rate of change for modifying the first adaptive parametersuch that the user responses are steered toward a neutral state aroundthe expected user response curve.
 2. The method of claim 1, wherein: theuser stimulus signal is an audio signal; the first adaptive parameter isan amplitude or level of the audio signal; and the second adaptiveparameter is a frequency of the audio signal.
 3. The method of claim 2,wherein the generated plurality of successive variations in the userstimulus signal are used to perform one or more of an audiometric test,a supra-threshold test, a psychometric tuning curve test, a maskedthreshold test, a temporal fine structure test, and a temporal maskingcurve test.
 4. The method of claim 3, wherein: the supra-threshold testis a masked threshold (MT) test; the MT test is measured for userstimulus noise probes with center frequencies between 500 Hz and 4 kHz,and at an audible sound level for the user; and a probe tone signal forthe user stimulus noise probe sweeps from 50% of the user stimulus noiseprobe center frequency to 150% of the user stimulus noise probe centerfrequency.
 5. The method of claim 1, further comprising modifying theexpected user response curve for the given user in response todetermining that the plurality of user responses do not exhibit aneutral state around an expected user response curve.
 6. The method ofclaim 5, wherein the instantaneous rate of change for modifying thefirst adaptive parameter is increased in response to determining thatone or more of the plurality of user responses will not reach a neutralstate around the expected user response curve.
 7. The method of claim 5,wherein the instantaneous rate of change for modifying the firstadaptive parameter is decreased in response to determining that one ormore of the plurality of user responses have exceeded the neutral statearound the expected user response curve.
 8. The method of claim 5,wherein the instantaneous rate of change for modifying the firstadaptive parameter is adjusted in order to create an equal time intervalbetween successive ones of the received plurality of user responses. 9.The method of claim 5, wherein the second adaptive parameter iscontinuously varied in order to steer the plurality of user responsestowards the neutral state around the expected user response curve. 10.The method of claim 1, wherein the second adaptive parameter iscontinuously varied monotonically across the one or more given ranges ofvalues.
 11. An auditory testing device comprising: at least oneprocessor; and at least one memory storing instructions, which whenexecuted cause the at least one processor to: generate a user stimulussignal according to a first adaptive parameter and a second adaptiveparameter; modify the first adaptive parameter in order to generate aplurality of successive variations in the user stimulus signal, suchthat the plurality of successive variations in the user stimulus signalare generated over one or more given ranges of values of the secondadaptive parameter; receive, in response to modifying the first adaptiveparameter, a plurality of user responses from a given user, each userresponse indicating that a corresponding one of the plurality ofsuccessive variations in the user stimulus signal has occurred; andbased at least in part on an expected user response curve for the givenuser and a calculated time interval between successive ones of theplurality of user responses received from the given user, adjust aninstantaneous rate of change for modifying the first adaptive parametersuch that the user responses are steered toward a neutral state aroundthe expected user response curve.
 12. The auditory testing device ofclaim 11, wherein: the user stimulus signal is an audio signal; thefirst adaptive parameter is an amplitude or level of the audio signal;and the second adaptive parameter is a frequency of the audio signal.13. The auditory testing device of claim 12, wherein the generatedplurality of successive variations in the user stimulus signal are usedto perform one or more of an audiometric test, a supra-threshold test, apsychometric tuning curve test, a temporal fine structure test, and atemporal masking curve test.
 14. The auditory testing device of claim13, wherein: the supra-threshold test is a masked threshold (MT) test;the MT test is measured for user stimulus noise probes with centerfrequencies between 500 Hz and 4 kHz, and at an audible sound level forthe user; and a probe tone signal for the user stimulus noise probesweeps from 50% of the user stimulus noise probe center frequency to150% of the user stimulus noise probe center frequency.
 15. The auditorytesting device of claim 11, wherein the instructions further cause theprocessor to modify the expected user response curve for the given userin response to determining that the plurality of user responses do notexhibit a neutral state around an expected user response curve.
 16. Theauditory testing device of claim 15, wherein the instantaneous rate ofchange for modifying the first adaptive parameter is increased inresponse to determining that one or more of the plurality of userresponses will not reach a neutral state around the expected userresponse curve.
 17. The auditory testing device of claim 15, wherein theinstantaneous rate of change for modifying the first adaptive parameteris decreased in response to determining that one or more of theplurality of user responses have exceeded the neutral state around theexpected user response curve.
 18. The auditory testing device of claim15, wherein the instantaneous rate of change for modifying the firstadaptive parameter is adjusted in order to create an equal time intervalbetween successive ones of the received plurality of user responses. 19.The auditory testing device of claim 15, wherein the second adaptiveparameter is continuously varied in order to steer the plurality of userresponses towards the neutral state around the expected user responsecurve.
 20. The auditory testing device of claim 11, wherein the secondadaptive parameter is continuously varied monotonically across the oneor more given ranges of values.